Cogmem Memory

Install and connect cogmem as a durable memory backend for OpenClaw. Version 2.5.1.

cogmem Memory Backend for OpenClaw

Use this skill when an OpenClaw workspace needs cogmem (the @CognitiveOS/core successor package) as its durable memory backend.

Ground Rules

• Use TOML config only: ~/.cogmem/config.toml or project .cogmem/config.toml.
• Do not create .agent-brain.env files.
• Do not pass --env-path.
• Do not configure kernel behavior through AB_*, COGMEM_*, or AGENT_BRAIN_MODEL_* environment variables.
• Do not import AGENTS.md, TOOLS.md, HEARTBEAT.md, or BOOTSTRAP.md; they are operational instructions, not durable user memory.
• Do not run a separate vector search before calling memory.recall(). KernelAgentMemoryBackend.recall() is the first-class recall path and already performs pulse activation, temporal traversal, graph traversal, and narrative assembly.

Install

Run from the OpenClaw workspace root:

bash

bun add "github:liuqin164/Cogmem#main"
./node_modules/.bin/cogmem-init --agent openclaw --scope project
./node_modules/.bin/cogmem-doctor

For a specific version:

bash

bun add "github:liuqin164/Cogmem#<commit>"

This creates project-local kernel config and storage under .cogmem/, which is the recommended OpenClaw workspace setup.

bash

./node_modules/.bin/cogmem-init --agent openclaw --scope project

The install creates:

text

.cogmem/config.toml
.cogmem/memory.db
.cogmem/snapshots/

Configure Embedding Model

To embed imported memories with a local quantized model, run Ollama locally and configure the kernel before importing:

bash

ollama pull qwen3-embedding:0.6b

toml

[core]
vector_dimension = 1024

[embedding]
provider = "openai_compatible"
base_url = "http://localhost:11434/v1"
model = "qwen3-embedding:0.6b"

Use the matching dimension for larger local models: qwen3-embedding:4b uses 2560; qwen3-embedding:8b uses 4096. Run ./node_modules/.bin/cogmem-doctor after editing. Imported records are embedded through the configured kernel embedder during cogmem-import-openclaw.

Migrate Existing OpenClaw Memory

Always preview first:

bash

./node_modules/.bin/cogmem-import-openclaw --workspace . --project openclaw --dry-run

Then migrate:

bash

./node_modules/.bin/cogmem-import-openclaw --workspace . --project openclaw

Use JSON output when another agent is orchestrating the run:

bash

./node_modules/.bin/cogmem-import-openclaw --workspace . --project openclaw --json

The importer is idempotent. Re-running it skips records already imported into the same memory database. Real non-JSON imports print source-level and embedding+ingest progress to stderr. Use --json --progress to keep JSON on stdout while streaming progress to stderr, or --no-progress when a wrapper needs quiet stderr.

Imported sources:

• USER.md as user profile memory.
• SOUL.md, PERSONA.md, and IDENTITY.md as persona/profile memory.
• MEMORY.md as imported summary/index memory.
• memory/YYYY-MM-DD.md and memory/YYYY-MM-DD-<slug>.md as daily episodic memory.
• sessions/*.md, session-logs/*.md, session_logs/*.md, conversations/*.md, exports/sessions/*.md, and exports/conversations/*.md as session memory.

Useful scoped imports:

bash

./node_modules/.bin/cogmem-import-openclaw --workspace . --project openclaw --date 2026-05-07
./node_modules/.bin/cogmem-import-openclaw --workspace . --project openclaw --session ./custom-session.md
./node_modules/.bin/cogmem-import-openclaw --workspace . --project openclaw --memory ./custom-memory.md
./node_modules/.bin/cogmem-import-openclaw --workspace . --project openclaw --session ./one.md --session ./two.md
./node_modules/.bin/cogmem-import-openclaw --workspace . --project openclaw --memory ./one.md --memory ./two.md

Runtime Wiring

Use KernelAgentMemoryBackend for turn storage and recall:

ts

import {
  KernelAgentMemoryBackend,
  createMemoryKernelFromConfig,
} from 'cogmem';

const kernel = createMemoryKernelFromConfig();
const memory = new KernelAgentMemoryBackend(kernel);

await memory.rememberTurn({
  agentId: 'openclaw',
  projectId: 'openclaw',
  sessionId,
  userText,
  assistantText,
});

const recall = memory.recall({
  agentId: 'openclaw',
  projectId: 'openclaw',
  query: userText,
});

const preparedContext = {
  mode: recall.recallMode,
  narrative: recall.narrative,
  pulseTrace: recall.pulseTrace,
  temporalLabels: recall.temporalTraversal?.labels,
  memories: recall.items,
};

Use recall.narrative as the compact prompt context and recall.items as cited memory evidence. If recall.recallMode === 'universe_navigation', the memory kernel has already prepared related context through the pulse/temporal/narrative path.

OpenClaw Host Integration Notes

cogmem-connect openclaw installs this file into <workspace>/skills/cogmem-memory/SKILL.md, which is OpenClaw's workspace skill location. That makes the procedure discoverable without changing OpenClaw host config.

Current OpenClaw memory config is OpenClaw-owned. Its documented backend selector is memory.backend with values such as "builtin" and "qmd", and the built-in memory surface exposes tools such as memory_search and memory_get. Do not write plugins.slots.memory or other unknown OpenClaw config fields for cogmem; OpenClaw uses strict config validation and unknown fields can prevent the Gateway from starting.

To make every future OpenClaw turn automatically use the memory kernel, install the local plugin wrapper:

bash

./node_modules/.bin/cogmem-connect openclaw --workspace . --auto --force

--auto writes <workspace>/extensions/cogmem-auto-memory/, patches plugins.load.paths, and enables hooks.allowPromptInjection=true and hooks.allowConversationAccess=true for the wrapper. The wrapper registers before_prompt_build for governed recall and agent_end for turn recording, then calls KernelAgentMemoryBackend through cogmem public API via a Bun bridge. cogmem does not import OpenClaw.

Queued remember is the default. agent_end appends a durable JSONL job under .cogmem/queue/openclaw-remember.jsonl and spawns a background drain process, so Telegram or gateway responses are not blocked by embeddings, SQLite writes, or slow local models. If a drain fails, the job is retried and then moved to a dead-letter file instead of being silently discarded.

After package updates or config drift, repair the host wiring:

bash

./node_modules/.bin/cogmem-doctor --fix --agent openclaw --workspace .

The wrapper maps OpenClaw behavior to cogmem like this:

• memory_search should call memory.recall() and return recall.narrative plus cited recall.items.
• memory_get should read from the cited evidence returned by core or from the original workspace file when a citation includes a file path.
• Prompt injection should use recall.narrative, not a raw vector nearest-neighbor dump.
• Turn capture should enqueue memory.rememberTurnWithResult() after the agent response. If OpenClaw exposes tool calls, tool results, or task events in the hook payload, the wrapper records them as ledger events with parent/child causality; if a result has no matching call, it is stored as a partial-causality task event instead of inventing a chain.

Debug Recall

Normal prompt injection stays compact. When a user asks where a memory came from, why it was recalled, or why another candidate was filtered, run:

bash

./node_modules/.bin/cogmem-explain-recall --query "<user question>" --project openclaw --agent openclaw --json

Inspect sourceAnchor, activationPath, whyMatched, filteredEvidence, and governanceReason. sourceAnchor points back to raw ledger events or imported source files. filteredEvidence is for audit/debug and must not be injected wholesale into normal prompts.

After runtime wiring changes, run:

bash

openclaw config schema
openclaw doctor
openclaw plugins inspect <plugin-id> --runtime --json
openclaw gateway restart

Dream Curator (Background Service)

The Dream Curator runs as a systemd user service for background memory consolidation:

bash

systemctl --user status cogmem-dream-curator
journalctl --user -u cogmem-dream-curator -n 20

Run manually:

bash

./node_modules/.bin/cogmem dream --project openclaw --watch --interval-ms 30000 --promote --json

MCP Bridge Option

If the OpenClaw environment exposes an MCP client, use the core MCP bridge instead of writing a native plugin first:

bash

./node_modules/.bin/cogmem-mcp

Expose these tools to the agent:

• cogmem_remember_turn
• cogmem_recall
• cogmem_explain_recall